24 posts found
The rise of predictive commerce: open data to anticipate needs
In a world where immediacy is becoming increasingly important, predictive commerce has become a key tool for anticipating consumer behaviors, optimizing decisions, and offering personalized experiences. It's no longer just about reacting to the customer's needs, it's about predicting what they…
How to ensure the authenticity of satellite imagery
Synthetic images are visual representations artificially generated by algorithms and computational techniques, rather than being captured directly from reality with cameras or sensors. They are produced from different methods, among which the antagonistic generative networks (Generative Adversarial…
PET technologies: how to use protected data in a privacy-sensitive way
As organisations seek to harness the potential of data to make decisions, innovate and improve their services, a fundamental challenge arises: how can data collection and use be balanced with respect for privacy? PET technologies attempt to address this challenge. In this post, we will explore what…
Using Pandas for quality error reduction in data repositories
There is no doubt that data has become the strategic asset for organisations. Today, it is essential to ensure that decisions are based on quality data, regardless of the alignment they follow: data analytics, artificial intelligence or reporting. However, ensuring data repositories with high levels…
Understanding Word Embeddings: how machines learn the meaning of words
Natural language processing (NLP) is a branch of artificial intelligence that allows machines to understand and manipulate human language. At the core of many modern applications, such as virtual assistants, machine translation and chatbots, are word embeddings. But what exactly are they and why are…
SLM, LLM, RAG and Fine-tuning: Pillars of Modern Generative AI
In the fast-paced world of Generative Artificial Intelligence (AI), there are several concepts that have become fundamental to understanding and harnessing the potential of this technology. Today we focus on four: Small Language Models(SLM), Large Language Models(LLM), Retrieval Augmented Generation…
Open data and generative AI: synergies and use cases
Artificial intelligence (AI) is revolutionising the way we create and consume content. From automating repetitive tasks to personalising experiences, AI offers tools that are changing the landscape of marketing, communication and creativity.
These artificial intelligences need to be trained wi…
RAG techniques: how they work and examples of use cases
In recent months we have seen how the large language models (LLMs ) that enable Generative Artificial Intelligence (GenAI) applications have been improving in terms of accuracy and reliability. RAG (Retrieval Augmented Generation) techniques have allowed us to use the full power of n…
GRAPH QL. Your best ally for the creation of data products.
The era of digitalisation in which we find ourselves has filled our daily lives with data products or data-driven products. In this post we discover what they are and show you one of the key data technologies to design and build this kind of products: GraphQL.
Introduction
Let's start at the beginni…
RAG - Retrieval Augmented Generation: The key that unlocks the door to precision language models
Teaching computers to understand how humans speak and write is a long-standing challenge in the field of artificial intelligence, known as natural language processing (NLP). However, in the last two years or so, we have seen the fall of this old stronghold with the advent of large language models (L…
